# 512-Dimensional Embedding

ConvNeXt-Nano face recognition model trained on the MS1MV3 dataset, compatible with the timm framework

A Vision Transformer (ViT) model trained on the MS1MV3 dataset, specifically designed for face recognition tasks.

A Vision Transformer (ViT) model trained on the MS1MV3 dataset, specifically designed for face recognition tasks

This is a model based on sentence-transformers that maps sentences and paragraphs into a 512-dimensional dense vector space, suitable for tasks like clustering or semantic search.

This is a model based on sentence-transformers that maps sentences and paragraphs into a 512-dimensional dense vector space, suitable for tasks such as clustering or semantic search.

This is a sentence-transformers-based model capable of mapping sentences and paragraphs into a 512-dimensional dense vector space, suitable for tasks like sentence similarity calculation, clustering, and semantic search.